公开(公告)号：US11599790B2

公开(公告)日：2023-03-07

申请号：US16614858

申请日：2017-07-21

Applicant: Landmark Graphics Corporation

Inventor： Yogendra Narayan Pandey ,  Keshava Prasad Rangarajan ,  Jeffrey Marc Yarus ,  Naresh Chaudhary ,  Nagaraj Srinivasan ,  James Etienne

IPC: G06N3/08 ,  G01V99/00 ,  G06K9/62

Abstract: Embodiments of the subject technology for deep learning based reservoir modelling provides for receiving input data comprising information associated with one or more well logs in a region of interest. The subject technology determines, based at least in part on the input data, an input feature associated with a first deep neural network (DNN) for predicting a value of a property at a location within the region of interest. Further, the subject technology trains, using the input data and based at least in part on the input feature, the first DNN. The subject technology predicts, using the first DNN, the value of the property at the location in the region of interest. The subject technology utilizes a second DNN that classifies facies based on the predicted property in the region of interest.

公开(公告)号：US20200160173A1

公开(公告)日：2020-05-21

申请号：US16614858

申请日：2017-07-21

Applicant: Landmark Graphics Corporation

Inventor： Yogendra Narayan Pandey ,  Keshava Prasad Rangarajan ,  Jeffrey Marc Yarns ,  Naresh Chaudhary ,  Nagaraj Srinivasan ,  James Etienne

IPC: G06N3/08 ,  G06K9/62 ,  G01V99/00

Abstract: Embodiments of the subject technology for deep learning based reservoir modelling provides for receiving input data comprising information associated with one or more well logs in a region of interest. The subject technology determines, based at least in part on the input data, an input feature associated with a first deep neural network (DNN) for predicting a value of a property at a location within the region of interest. Further, the subject technology trains, using the input data and based at least in part on the input feature, the first DNN. The subject technology predicts, using the first DNN, the value of the property at the location in the region of interest. The subject technology utilizes a second DNN that classifies facies based on the predicted property in the region of interest.